Stephanie Valarezo

AI agents deliver value when powered by real-time data with the right context. Yet, many organizations still rely on outdated or fragmented information, limiting AI impact and increasing risk. In this session, learn how to deliver real-time data as AI-ready context across structured and unstructured sources in hybrid environments to maximize the value of your Snowflake investments. See how streaming and historical data integration enable governed data to flow into and out of Snowflake, reducing data movement and supporting processing where data lives. Discover real-time integration, governance and an open hybrid data foundation work together to power AI agents and your business.

As AI adoption accelerates, unstructured data has emerged as a critical—yet often overlooked—asset for building accurate, trustworthy AI agents. But preparing and governing this data at scale remains a challenge. Traditional data integration and RAG approaches fall short. In this session, discover how IBM enables AI agents grounded in governed, high-quality unstructured data. Learn how our unified data platform streamlines integration across batch, streaming, replication, and unstructured sources—while accelerating data intelligence through built-in governance, quality, lineage, and data sharing. But governance doesn’t stop at data. We’ll explore how AI governance extends oversight to the models and agents themselves. Walk away with practical strategies to simplify your stack, strengthen trust in AI outputs, and deliver AI-ready data at scale.